Evidence map›Paper›PMID 40594638›Full record

ArticleScientific reports2025

Spatiotemporal distribution of sustained dengue hotspots associated with climate and urbanisation in Singapore.

Murali Krishna Gurram, Sylvia Gwee, Yi-Chen Wang, Junxiong Pang

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Murali Krishna GurramSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore.
Sylvia GweeSaw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore.
Yi-Chen WangDepartment of Geography, Faculty of Arts and Social Sciences, National University of Singapore, Singapore, Singapore.
Junxiong PangSingHealth Duke-NUS Global Health Institute, Singapore, Singapore. vincentpang@duke-nus.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to explore the spatiotemporal dynamics of sustained dengue hotspots in relation to climatic and urbanization factors in Singapore. Geographically Weighted Regression (GWR) model was employed to evaluate monthly dengue incidence and associated spatiotemporal hotspot patterns between May 2013 and March 2020. The combination of rainfall, temperature, population density, urbanization, building age and flood vulnerability was significantly correlated with dengue incidence in different subzones of Singapore. GWR results from 2013 to 2020 repeatedly (> 10 times) identified around 19 subzones of significance, where dengue incidence was highly influenced by a combination of population, climatic and urbanisation factors. The study found the distribution of dengue most prominently in the central and the eastern regions of Singapore. Majority of the highly significant subzones belonged to the east region (n = 8), covering 3.22% of the total area and a population of 512,680, followed by north-eastern subzones (n = 4) covering 0.92% of the total area with a population of 125,490, central subzones (n = 4) covering 1.22% of the total area with a population of 109,440, northern subzones (n = 2) with 0.52% of total area with a population of 152,860 and a subzone in the west covering 0.28% of total area with a population of 68,840. The study demonstrates potential application of GWR model with GIS for identifying sustained dengue hotspots in Singapore.

Indexed as

ClimateDengueUrbanizationHumansIncidenceSingaporeSpatio-Temporal AnalysisDengue incidenceDisease mapping and surveillanceSpatiotemporal analysis

Identifiers

PMID40594638
PMCPMC12214785

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.